Paul Smolensky is Krieger-Eisenhower Professor of Cognitive Science at the Johns Hopkins University and a Senior Principal Researcher at Microsoft Research, Redmond Washington.
James D. McCaffrey is an American research software engineer at Microsoft Research known for his contributions to machine learning, combinatorics, and software test automation.
MIX was a Microsoft conference held annually for Web developers and designers at which Microsoft showcased upcoming web technologies. The conference was held each spring at the Venetian Hotel in Las Vegas. Unlike many of Microsoft's technical conference, MIX has been promoted more heavily to designers by inviting popular speakers from other popular web design conferences, such as SXSW, and has sponsored a CSS design contest each year to promote the conference. Microsoft has also used this conference as an opportunity to promote new web design and development tools such as Silverlight and Microsoft Expression Studio.
Deep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised.
Eclipse Deeplearning4j is a programming library written in Java for the Java virtual machine (JVM). It is a framework with wide support for deep learning algorithms. Deeplearning4j includes implementations of the restricted Boltzmann machine, deep belief net, deep autoencoder, stacked denoising autoencoder and recursive neural tensor network, word2vec, doc2vec, and GloVe. These algorithms all include distributed parallel versions that integrate with Apache Hadoop and Spark.
TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks.
The following table compares notable software frameworks, libraries and computer programs for deep learning.
Keras is an open-source software library that provides a Python interface for artificial neural networks. Keras acts as an interface for the TensorFlow library.
Apache MXNet is an open-source deep learning software framework, used to train and deploy deep neural networks. It is scalable, allowing for fast model training and supports a flexible programming model and multiple programming languages. The MXNet library is portable and can scale to multiple GPUs as well as multiple machines. It was co-developed by Carlos Guestrin at University of Washington.
AMD Instinct is AMD's brand of professional GPUs. It replaced AMD's FirePro S brand in 2016. Compared to the Radeon brand of mainstream consumer/gamer products, the Instinct product line is intended to accelerate deep learning, artificial neural network, and high-performance computing/GPGPU applications.
Chainer is an open source deep learning framework written purely in Python on top of NumPy and CuPy Python libraries. The development is led by Japanese venture company Preferred Networks in partnership with IBM, Intel, Microsoft, and Nvidia.
Caffe is a deep learning framework, originally developed at University of California, Berkeley. It is open source, under a BSD license. It is written in C++, with a Python interface.
Stephen John Young is a British researcher, Professor of Information Engineering at the University of Cambridge and an entrepreneur. He is one of the pioneers of automated speech recognition and statistical spoken dialogue systems. He served as the Senior Pro-Vice-Chancellor of the University of Cambridge from 2009 to 2015, responsible for planning and resources. From 2015 to 2019, he held a joint appointment between his professorship at Cambridge and Apple, where he was a senior member of the Siri development team.
PyTorch is a machine learning framework based on the Torch library, used for applications such as computer vision and natural language processing, originally developed by Meta AI and now part of the Linux Foundation umbrella. It is free and open-source software released under the modified BSD license. Although the Python interface is more polished and the primary focus of development, PyTorch also has a C++ interface.
The Open Neural Network Exchange (ONNX) [] is an open-source artificial intelligence ecosystem of technology companies and research organizations that establish open standards for representing machine learning algorithms and software tools to promote innovation and collaboration in the AI sector. ONNX is available on GitHub.
ML.NET is a free software machine learning library for the C# and F# programming languages. It also supports Python models when used together with NimbusML. The preview release of ML.NET included transforms for feature engineering like n-gram creation, and learners to handle binary classification, multi-class classification, and regression tasks. Additional ML tasks like anomaly detection and recommendation systems have since been added, and other approaches like deep learning will be included in future versions.
OpenVINO toolkit is a free toolkit facilitating the optimization of a deep learning model from a framework and deployment using an inference engine onto Intel hardware. The toolkit has two versions: OpenVINO toolkit, which is supported by open source community and Intel Distribution of OpenVINO toolkit, which is supported by Intel. OpenVINO was developed by Intel. The toolkit is cross-platform and free for use under Apache License version 2.0. The toolkit enables a write-once, deploy-anywhere approach to deep learning deployments on Intel platforms, including CPU, integrated GPU, Intel Movidius VPU, and FPGAs.
NNI is a free and open-source AutoML toolkit developed by Microsoft. It is used to automate feature engineering, model compression, neural architecture search, and hyper-parameter tuning.
VoTT is a free and open source electron app for image annotation and labeling developed by Microsoft. The software is written in the TypeScript programming language and used for building end to end object detection models from image and videos assets for computer vision algorithms.
